Revolutionizing Timber Structures: A Comprehensive Review on AI-Driven Structural Design, Performance Optimization, and Future Perspectives

Girmay Mengesha Azanaw*
Periodicity:January - March'2025

Abstract

This comprehensive review examines the transformative impact of artificial intelligence (AI) on timber structural engineering, emphasizing advancements in AI-driven design, performance optimization, and future directions. Timber has experienced a renaissance as a sustainable construction material, bolstered by the development of engineered wood products such as Cross- Laminated Timber (CLT) and glued laminated timber (Glulam). These products offer enhanced structural performance, aesthetic versatility, and environmental benefits. However, traditional timber design methods, which largely rely on empirical approaches, are increasingly inadequate for addressing modern performance demands and complex architectural geometries. AI techniques, including machine learning, deep learning, and genetic algorithms, are revolutionizing timber engineering by enabling precise material characterization, load path optimization, and real-time failure prediction. By integrating these methods with conventional finite element analysis (FEA), researchers have significantly reduced computation times while improving simulation accuracy. Furthermore, the incorporation of sensor-based data acquisition and Building Information Modeling (BIM) facilitates dynamic monitoring and predictive maintenance, ensuring long-term structural integrity. This review synthesizes literature on AI applications in timber design, detailing the evolution from traditional methods to current digital practices. It discusses the benefits and challenges of integrating AI into simulation workflows, performance monitoring, and digital fabrication processes. Additionally, the paper outlines future research opportunities, including multi-scale modeling, sustainability lifecycle assessments, and the development of adaptive, integrated design systems that fully leverage AI capabilities. Overall, our analysis highlights the potential of AI-driven frameworks to enhance the safety, efficiency, and sustainability of timber structures, providing a roadmap for future innovations in the field. By bridging the gap between traditional construction practices and advanced computational technologies, this review offers valuable insights for researchers, engineers, and practitioners dedicated to advancing modern timber engineering.

Keywords

imber Structures, Artificial Intelligence, Structural Optimization, Digital Fabrication, Sustainable Construction

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